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Orthogonal Statistical Learning

25 January 2019

Papers citing "Orthogonal Statistical Learning"

44 / 44 papers shown

Title
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner Valentyn Melnychuk Stefan Feuerriegel Mihaela van der Schaar CML 253 5 0 05 Nov 2024
Automatic debiasing of neural networks via moment-constrained learning Christian L. Hines Oliver J. Hines CML OOD 136 0 0 29 Sep 2024
Model-agnostic meta-learners for estimating heterogeneous treatment effects over time Dennis Frauen Konstantin Hess Stefan Feuerriegel 153 7 0 07 Jul 2024
Orthogonal Causal Calibration Justin Whitehouse Christopher Jung Vasilis Syrgkanis Bryan Wilder Zhiwei Steven Wu CML 163 1 0 04 Jun 2024
Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning Yihong Gu Cong Fang Peter Bühlmann Jianqing Fan OOD CML 301 2 0 07 May 2024
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation Jikai Jin Vasilis Syrgkanis CML 198 1 0 22 Feb 2024
Selective Uncertainty Propagation in Offline RL Sanath Kumar Krishnamurthy Shrey Modi Tanmay Gangwani S. Katariya Branislav Kveton A. Rangi OffRL 207 0 0 01 Feb 2023
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruosong Wang MLT 227 974 0 24 Jan 2019
Robust Estimation of Causal Effects via High-Dimensional Covariate Balancing Propensity Score Y. Ning Sida Peng Kosuke Imai 61 87 0 20 Dec 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 205 775 0 12 Nov 2018
Offline Multi-Action Policy Learning: Generalization and Optimization Zhengyuan Zhou Susan Athey Stefan Wager OffRL 67 122 0 10 Oct 2018
Deep Neural Networks for Estimation and Inference M. Farrell Tengyuan Liang S. Misra BDL 186 255 0 26 Sep 2018
Local Linear Forests R. Friedberg J. Tibshirani Susan Athey Stefan Wager 152 92 0 30 Jul 2018
Optimization over Continuous and Multi-dimensional Decisions with Observational Data Dimitris Bertsimas Christopher McCord 119 27 0 11 Jul 2018
Regularized Orthogonal Machine Learning for Nonlinear Semiparametric Models Denis Nekipelov Vira Semenova Vasilis Syrgkanis 85 20 0 13 Jun 2018
Orthogonal Random Forest for Causal Inference Miruna Oprescu Vasilis Syrgkanis Zhiwei Steven Wu CML 110 111 0 09 Jun 2018
Logistic Regression: The Importance of Being Improper Dylan J. Foster Satyen Kale Haipeng Luo M. Mohri Karthik Sridharan 66 78 0 25 Mar 2018
De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers Victor Chernozhukov Whitney Newey Rahul Singh 85 92 0 23 Feb 2018
Policy Evaluation and Optimization with Continuous Treatments Nathan Kallus Angela Zhou OffRL 161 137 0 16 Feb 2018
Size-Independent Sample Complexity of Neural Networks Noah Golowich Alexander Rakhlin Ohad Shamir 161 551 0 18 Dec 2017
Quasi-Oracle Estimation of Heterogeneous Treatment Effects Xinkun Nie Stefan Wager CML 176 655 0 13 Dec 2017
Orthogonal Machine Learning: Power and Limitations Lester W. Mackey Vasilis Syrgkanis Ilias Zadik 201 42 0 01 Nov 2017
Spectrally-normalized margin bounds for neural networks Peter L. Bartlett Dylan J. Foster Matus Telgarsky ODL 218 1,225 0 26 Jun 2017
Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning Sören R. Künzel Jasjeet Sekhon Peter J. Bickel Bin Yu CML 185 930 0 12 Jun 2017
Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks Peter L. Bartlett Nick Harvey Christopher Liaw Abbas Mehrabian 222 434 0 08 Mar 2017
Policy Learning with Observational Data Susan Athey Stefan Wager CML OffRL 447 183 0 09 Feb 2017
Generalized Random Forests Susan Athey J. Tibshirani Stefan Wager 353 1,371 0 05 Oct 2016
Locally Robust Semiparametric Estimation Victor Chernozhukov J. Escanciano Hidehiko Ichimura Whitney Newey J. M. Robins 115 210 0 29 Jul 2016
A vector-contraction inequality for Rademacher complexities Andreas Maurer 87 261 0 01 May 2016
Learning with Square Loss: Localization through Offset Rademacher Complexity Tengyuan Liang Alexander Rakhlin Karthik Sridharan 101 75 0 21 Feb 2015
Counterfactual Risk Minimization: Learning from Logged Bandit Feedback Adith Swaminathan Thorsten Joachims OffRL 153 167 0 09 Feb 2015
Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models Xiaohong Chen Demian Pouzo 71 111 0 05 Nov 2014
Learning without Concentration S. Mendelson 253 334 0 01 Jan 2014
Program Evaluation and Causal Inference with High-Dimensional Data A. Belloni Victor Chernozhukov Iván Fernández-Val Christian B. Hansen CML 236 359 0 11 Nov 2013
Empirical entropy, minimax regret and minimax risk Alexander Rakhlin Karthik Sridharan Alexandre B. Tsybakov 203 82 0 06 Aug 2013
Learning subgaussian classes : Upper and minimax bounds Guillaume Lecué S. Mendelson 153 86 0 21 May 2013
Global risk bounds and adaptation in univariate convex regression Adityanand Guntuboyina B. Sen 99 81 0 07 May 2013
Domain Adaptation for Statistical Classifiers Hal Daumé D. Marcu OOD 109 912 0 28 Sep 2011
Performance guarantees for individualized treatment rules Min Qian Susan Murphy 329 559 0 17 May 2011
Doubly Robust Policy Evaluation and Learning Miroslav Dudík John Langford Lihong Li OffRL 349 698 0 23 Mar 2011
Optimistic Rates for Learning with a Smooth Loss Nathan Srebro Karthik Sridharan Ambuj Tewari 173 283 0 20 Sep 2010
Empirical Bernstein Bounds and Sample Variance Penalization Andreas Maurer Massimiliano Pontil 418 545 0 21 Jul 2009
Domain Adaptation: Learning Bounds and Algorithms Yishay Mansour M. Mohri Afshin Rostamizadeh 307 801 0 19 Feb 2009
The Offset Tree for Learning with Partial Labels A. Beygelzimer John Langford 341 185 0 21 Dec 2008